Path Planning Usage for Autonomous Agents
DOI:
https://doi.org/10.17770/etr2013vol2.867Keywords:
robotic, Simulated Annealing, path planningAbstract
In order to achieve the wide range of the robotic application it is necessary to provide iterative motions among points of the goals. For instance, in the industry mobile robots can replace any components between a storehouse and an assembly department. Ammunition replacement is widely used in military services. Working place is possible in ports, airports, waste site and etc. Mobile agents can be used for monitoring if it is necessary to observe control points in the secret place. The paper deals with path planning programme for mobile robots. The aim of the research paper is to analyse motion-planning algorithms that contain the design of modelling programme. The programme is needed as environment modelling to obtain the simulation data. The simulation data give the possibility to conduct the wide analyses for selected algorithm. Analysis means the simulation data interpretation and comparison with other data obtained using the motion-planning. The results of the careful analysis were considered for optimal path planning algorithms. The experimental evidence was proposed to demonstrate the effectiveness of the algorithm for steady covered space. The results described in this work can be extended in a number of directions, and applied to other algorithms.Downloads
References
E. Aarts and J. Korst. Simulated annealing and Boltzman machines: A stochastic approach to combinatorial optimization and neural computing. John Wiley and Sons, 1989.
D. L. Applegate, R. E. Bixby, V. Chvátal and W.J. Cook, The Traveling Salesman Problem, Princeton University Press, Princeton, USA, 2007.
W. J. Cook, In Pursuit of the Traveling Salesman. Princeton University Press, Princeton, USA 2011.
D. Davendra, Traveling Salesman Problem, Theory and Applications. InTech, Rijeka, Croatia, 2010.
R.H.J.M. Otten and L.P.P.P. Ginneken, The Annealing Algorithm. Kluwer Academic Publishers, 1989.
R. Siegwart, I. R. Nourbakhsh and D. Scaramuzza, Introduction to Autonomous Mobile Robots. A Bradford Book The MIT Press Cambridge, Massachusetts London, England, 2011.
P. H. Batavia and I. Nourbakhsh, Path planning for the Cye personal robot, IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS), 2000.
R. Biswas, B. Limketaki, S. Sanner and S. Thrun, Towards Object Mapping in Dynamic Environments with Mobile Robots, Proceedings of the Conference on Intelligent Robots and Systems (IROS), Lausanne, Switzerland, 2002.
M. Dorigo and L. M. Gambardella, “Ant Colonies for the Traveling Salesman Problem,” University Libre de Bruxelles, Belgium, 1996.
D. S. Johnson and L. A. McGeoch, “The Traveling Salesman Problem: A Case Study in Local Optimization.” in E. H. L. Aarts and J. K. Lenstra (editors), John Wiley and Sons, Ltd., 1997, pp. 215-310.
V. Ashkenazi, D. Park and M. Dumville, “Robot Positioning and the Global Navigation Satellite System,” Industrial Robots: An International Journal, 27(6), pp. 419-426, 2000.
J. Buhmann, W. Burgard, A. B. Cremers, D. Fox, T. Hofmann, F. Schneider, J. Strikos and S. Thrun, “The Mobile Robot Rhino,” AI Magazine, 16(1), 1995.
H. Choset, “Coverage of Known Spaces: The Boustrophedon Cellular Decomposition, in Autonomous Robots,” 9:247-253, Kluwer, 2000.
E. W. Dijkstra, “A note on two problems in connexion with graphs,” Numerische Mathematik, v. 1, p. 269-271, 1959.
S. Kirkpatrick, “Optimization by Simulated Annealing: Quantitative Studies,” Journal of Statistical Physics, 34, pp. 975-986, 1984.
S. Kirkpatrick, C. D. Gelatt and M. P. Vecchi, “Optimization by Simulated Annealing,” Science, 220, pp. 671-680, 1983.
E. Valbahs and P. Grabusts, “Motion Planning of an Autonomous Robot in Closed Space with Obstacles,” Scientific Journal of RTU. 5. series., Datorzinatne. - 15. vol., pp. 52-57, 2012.
M. P. Vecchi and S. Kirkpatrick, “Global Wiring by Simulated Annealing,” IEEE Transaction on Computer Aided Design, CAD-2, pp. 215-222, 1983.